Open AccessCell–cell interaction networks regulate blood stem and progenitor cell fate
Author(s) -
Kirouac Daniel C,
Madlambayan Gerard J,
Yu Mei,
Sykes Edward A,
Ito Caryn,
Zandstra Peter W
Publication year - 2009
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.1038/msb.2009.49
Subject(s) - biology , microbiology and biotechnology , cell fate determination , progenitor cell , stem cell , cell , in silico , intracellular , multicellular organism , haematopoiesis , cell type , cellular differentiation , cell signaling , blood cell , signal transduction , immunology , transcription factor , genetics , gene
Communication networks between cells and tissues are necessary for homeostasis in multicellular organisms. Intercellular (between cell) communication networks are particularly relevant in stem cell biology, as stem cell fate decisions (self‐renewal, proliferation, lineage specification) are tightly regulated based on physiological demand. We have developed a novel mathematical model of blood stem cell development incorporating cell‐level kinetic parameters as functions of secreted molecule‐mediated intercellular networks. By relation to quantitative cellular assays, our model is capable of predictively simulating many disparate features of both normal and malignant hematopoiesis, relating internal parameters and microenvironmental variables to measurable cell fate outcomes. Through integrated in silico and experimental analyses, we show that blood stem and progenitor cell fate is regulated by cell–cell feedback, and can be controlled non‐cell autonomously by dynamically perturbing intercellular signalling. We extend this concept by demonstrating that variability in the secretion rates of the intercellular regulators is sufficient to explain heterogeneity in culture outputs, and that loss of responsiveness to cell–cell feedback signalling is both necessary and sufficient to induce leukemic transformation in silico.